{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a5d369dc-db3a-4afe-aaac-8ff2a113adb8",
   "metadata": {},
   "source": [
    "pie 函数是 Matplotlib 中用于绘制饼图（Pie Chart）的函数。它用于可视化数据的相对比例，常用于显示类\r\n",
    "别数据的占比关系。以下是该函数的参数说明："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06a1e620-2daf-4576-a206-e12d482cc8c5",
   "metadata": {},
   "source": [
    "x：要绘制的数据，通常是一个列表或数组，表示各个类别的数量或比例。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cafc719-9866-4c77-a239-896fb1aaa9ca",
   "metadata": {},
   "source": [
    "explode：可选参数，用于指定是否要将某个扇形分离出来。默认为 None，表示不分离，如果要分离某个\r\n",
    "扇形，可以传入一个与数据长度相同的列表或数组，其中非分离的扇形对应位置的值为 0，要分离的扇形\r\n",
    "对应位置的值大于 0。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a468b999-a361-4746-9164-fda6f62da9b7",
   "metadata": {},
   "source": [
    "labels：可选参数，用于指定每个扇形的标签文本。默认为 None，表示不显示标签。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cdcf32a-dc54-4d91-8dcc-6a7be2b99257",
   "metadata": {},
   "source": [
    "colors：可选参数，用于指定每个扇形的颜色。可以传入一个颜色列表，长度与数据 x 相同，或者使用\r\n",
    "Matplotlib 的颜色映射（colormap）来自动分配颜色"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93d486bc-27fd-4d50-89b3-bd276b2ec287",
   "metadata": {},
   "source": [
    "autopct：可选参数，用于指定扇形上显示的百分比文本格式。默认为 None，表示不显示百分比。如果要\r\n",
    "显示百分比，可以传入一个格式字符串，例如 \"%1.1f%%\"。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a661641-0cd2-4eff-86ea-0f6c79186feb",
   "metadata": {},
   "source": [
    "pctdistance：可选参数，用于指定百分比文本距离圆心的距离，取值范围为 [0, 1]，默认为 0.6。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db4c1071-474f-4871-9043-8c63ea97588f",
   "metadata": {},
   "source": [
    "shadow：可选参数，是否在饼图下方添加阴影，默认为 False。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7fc5485-4695-4b48-8db7-602c2b9b093d",
   "metadata": {},
   "source": [
    "labeldistance：可选参数，用于指定标签文本距离圆心的距离，取值范围为 [0, 1]，默认为 1.1。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b14994bb-5d2a-40e8-ae9c-4ce47d2e2032",
   "metadata": {},
   "source": [
    "startangle：可选参数，用于指定起始角度，默认为 0 度，表示从正上方开始逆时针绘制扇形。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75517781-9515-4449-9fd4-ed001d5450cc",
   "metadata": {},
   "source": [
    "radius：可选参数，用于指定饼图的半径，默认为 1。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62594fe2-5fcf-4dc8-8aac-6cbd22b299e3",
   "metadata": {},
   "source": [
    "counterclock：可选参数，是否逆时针绘制扇形，默认为 True，表示逆时针。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00f64460-cdf5-40f2-9df4-cffcfb1ec8b3",
   "metadata": {},
   "source": [
    "wedgeprops：可选参数，一个字典，用于指定扇形的属性，例如边界线样式等。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35b31128-6a0a-488c-883d-85f867401f00",
   "metadata": {},
   "source": [
    "textprops：可选参数，一个字典，用于指定标签文本的属性，例如字体大小、颜色等。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "597412e9-da1f-4d90-87a5-bc18a1d2910d",
   "metadata": {},
   "source": [
    "center：可选参数，一个元组 (x, y)，用于指定饼图的中心位置，默认为 (0, 0)。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "433a4824-320c-4cdc-9743-c84c6873026a",
   "metadata": {},
   "source": [
    "frame：可选参数，是否绘制饼图的外边框，默认为 False。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "371f9e8c-fd54-4d59-bbdc-4f2d365d53d8",
   "metadata": {},
   "source": [
    "rotatelabels：可选参数，是否旋转标签文本以适应扇形的布局，默认为 False。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3f9beaa-4f82-4bf9-adc9-144bd2a4da7a",
   "metadata": {},
   "source": [
    "normalize：可选参数，是否将数据归一化为百分比，如果设置为 True，则 x 中的数据会被归一化为百分\r\n",
    "比，总和为 100%。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e49a103e-b570-4e1a-baa1-e3b7e043fce9",
   "metadata": {},
   "source": [
    "hatch：可选参数，用于指定扇形的填充图案，例如 '/'、'\\\\' 等。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bd67214-98b5-4f6d-8d5a-aaa8ff259814",
   "metadata": {},
   "source": [
    "data：可选参数，一个 Pandas DataFrame，用于指定数据来源，可以替代 x 参数。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87480d56-4a04-4338-8d16-818d97c71604",
   "metadata": {},
   "source": [
    "在 Matplotlib 中，hatch 参数用于指定饼图或柱状图中填充的图案样式。以下是一些常用的 hatch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38b54ce0-9338-4cc4-a9d7-397d2c0c3e2f",
   "metadata": {},
   "source": [
    "1. '/'：斜线填充。\r\n",
    "2. '\\\\'：反斜线填充。\r\n",
    "3. '|'：竖线填充。\r\n",
    "4. '‐'：横线填充。\r\n",
    "5. '+'：交叉线填充。\r\n",
    "6. 'x'：叉形填充。\r\n",
    "7. 'o'：圆形填充。\r\n",
    "8. '.'：点状填充。\r\n",
    "9. '*'：星形填充。\r\n",
    "10. 'O'：大圆形填充。\r\n",
    "11. 'X'：大叉形填充。\r\n",
    "12. '\\\\\\\\'：双反斜线填充"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3341c618-8be2-44e2-9458-97192dea7f67",
   "metadata": {},
   "source": [
    "1 基础饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3ae54cf5-e0c5-4bc8-8d07-22815387cf78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotx\n",
    "from pyecharts import faker        # 不明白faker是什么，为啥labels，colors和sizes都有\n",
    "labels = faker.Faker.week_en\n",
    "colors = [faker.Faker.rand_color() for _ in range(7)]\n",
    "sizes = faker.Faker.values()\n",
    "explode = (0.1,0.1,0.1,0.1,0.1,0.1,0.1)\n",
    "\n",
    "# 使用matplotx的‘pitaya_smoothie’样式\n",
    "with plt.style.context(matplotx.styles.pitaya_smoothie['light']):\n",
    "    # 创建一个图形窗口，设置大小和分辨率\n",
    "    plt.figure(figsize=(8,6),dpi=100)\n",
    "    # 绘制饼图\n",
    "    plt.pie(\n",
    "        sizes,   # 扇形大小\n",
    "        labels=labels, # 扇形标签\n",
    "        colors=colors,  # 扇形颜色\n",
    "        autopct='%.2f%%',  # 百分比文本格式\n",
    "        startangle=90,   # 逆时针起始角度设置\n",
    "        pctdistance=0.7,  # 数据据圆心半径倍数距离\n",
    "        shadow=False,   # 是否添加阴影，阴影设计，建议设定True或False\n",
    "        explode=explode,  # 分离指定扇形\n",
    "        radius=1,  # 缩放系统\n",
    "       # hatch='*',  # 系统填充样式\n",
    "        frame=True   # 是否绘制边框\n",
    "    )\n",
    "    # 设置x和y轴的限制范围\n",
    "    plt.xlim(-2,2)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d28c79d3-6906-423f-93cd-f07cc45e37a2",
   "metadata": {},
   "source": [
    "2 进阶饼图-子图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6d6db45c-3525-4f55-8190-8f9649689b29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotx\n",
    "\n",
    "from matplotlib.patches import ConnectionPatch\n",
    "# 从matplotlib导入ConnectionPatch类，用于连接两张图表\n",
    "\n",
    "# 饼图参数\n",
    "overall_ratios = [.27,.56,.17]  # 定义饼图数据   定义一个列表，包含饼图的三部分比例\n",
    "labels = ['Approve','Disapprove','Undecided']  # 定义饼图标签，【‘支持’，‘反对’，‘未决定’】\n",
    "# 定义一个列表，包含饼图的标签\n",
    "explode=[0.1,0,0]  # 定义饼图突出显示   定义一个列表，用于设置饼图中各部分中突出显示层度\n",
    "\n",
    "# 条形图参数\n",
    "age_ratios = [.33,.54,.07,.06]  # 条形图各组数据   定义一个列表，包含条形图的四组数据比例\n",
    "age_labels = ['Under 35','35-49','50-65','Over 65']  # 条形图标签  定义一个列表，包含条形图标签\n",
    "\n",
    "with plt.style.context(matplotx.styles.pitaya_smoothie['light']):\n",
    "    # 创建一个图形窗口，设置大小和分辨率\n",
    "    # 创建图像和坐标轴\n",
    "    fig,(ax1,ax2) = plt.subplots(1,2,figsize=(9,5))  # 创建1行2列子图，并获取坐标轴\n",
    "    # 创建一个包含一行两列子图的图形，并返回两个坐标轴对象\n",
    "    fig.subplots_adjust(wspace=0)  # 调整子图间距为0\n",
    "    # 旋转饼图，使第一块位于x轴上\n",
    "    angle = -180*overall_ratios[0]  # 计算饼图的起始角度，使第一快位于x轴上\n",
    "    wedges, *_=ax1.pie(overall_ratios,autopct='%1.1f%%',startangle=angle,labels=labels,\n",
    "                      explode=explode,)  # 绘制饼图，并返回饼图的楔形块对象列表\n",
    "    bottom = 1   # 条形图基准线位置\n",
    "    width = .2  # 条形图宽度\n",
    "    # 从上向下绘制，以匹配图例顺序\n",
    "    for j,(height,label) in enumerate(reversed(list(zip(age_ratios,age_labels)))):\n",
    "        bottom -= height  # 计算每个条形底部位置\n",
    "        bc = ax2.bar(0,height,width,bottom=bottom,color='red',label=label,alpha=0.1+0.25*j)\n",
    "        # 绘制条形图\n",
    "        ax2.bar_label(bc,labels=[f\"{height:.0%}\"],label_type='center')\n",
    "        # 添加数据标签\n",
    "    ax2.set_title('age of approvers')  # 设置标签\n",
    "    ax2.legend(loc=1,bbox_to_anchor=(1.2,0.9,0,0),) # 显示图例\n",
    "    ax2.axis('off') # 隐藏坐标轴\n",
    "    ax2.set_xlim(-2.5 * width,2.5 * width) # 设置x轴范围\n",
    "\n",
    "    # 使用connectionpatch在两张表间添加连接线\n",
    "    theta1,theta2 = wedges[0].theta1,wedges[0].theta2  # 获取饼图中两条边界角度\n",
    "    center,r = wedges[0].center,wedges[0].r  # 获取饼图圆心和半径\n",
    "\n",
    "    bar_height = sum(age_ratios)  # 条形图总高度\n",
    "\n",
    "    # 绘制上部连接线\n",
    "    x = r * np.cos(np.pi / 180*theta2) + center[0]\n",
    "    y = r * np.sin(np.pi / 180*theta2) + center[1]\n",
    "    con = ConnectionPatch(xyA = (-width/2,bar_height),coordsA=ax2.transData,\n",
    "                         xyB = (x,y),coordsB=ax1.transData)\n",
    "    con.set_color([0,0,0])  # 设置连接线颜色\n",
    "    con.set_linewidth(2)  # 设置连接线宽度\n",
    "    ax2.add_artist(con)   # 添加连接线到坐标轴\n",
    "\n",
    "    # 绘制下部连接线\n",
    "    x = r * np.cos(np.pi / 180*theta1) + center[0]\n",
    "    y = r * np.sin(np.pi / 180*theta1) + center[1]\n",
    "    con = ConnectionPatch(xyA=(-width/2,0),coordsA=ax2.transData,\n",
    "                         xyB=(x,y),coordsB=ax1.transData)\n",
    "    con.set_color([0,0,0])\n",
    "    ax2.add_artist(con)\n",
    "    con.set_linewidth(2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aae26ac8-f891-4167-9a89-16726515a077",
   "metadata": {},
   "source": [
    "ConnectionPatch 是 Matplotlib 中的一个图形元素，用于在图中创建连接线，将两个对象（例如两个子图、\r\n",
    "两个点等）连接起来。它通常用于创建图中的注释、箭头、连接线等"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c59b39c0-6edd-4265-bbd1-2ded82a2c488",
   "metadata": {},
   "source": [
    "以下是 ConnectionPatch 的主要参数说明："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc6b4389-9c2c-4414-b44b-d2455abd1c45",
   "metadata": {},
   "source": [
    "xyA：连接线的起始点的坐标，通常是一个元组 (x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7793d791-4ca9-4d48-9807-8476e05821e9",
   "metadata": {},
   "source": [
    "coordsA：指定 xyA 的坐标系，可以是 'data'（数据坐标系）或其他坐标系"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef5bf641-80e9-4810-a455-cbeb1258bbd6",
   "metadata": {},
   "source": [
    "xyB：连接线的结束点的坐标，通常也是一个元组 (x, y)。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b745952-0bc7-4981-a448-4e4e70dc5722",
   "metadata": {},
   "source": [
    "coordsB：指定 xyB 的坐标系，可以是 'data'（数据坐标系）或其他坐标系。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db6fdfea-b008-4f6c-914c-4a32f52277d7",
   "metadata": {},
   "source": [
    "arrowstyle：可选参数，指定连接线的箭头样式，可以是各种箭头样式的字符串，例如 '‐>' 表示带有箭\r\n",
    "头的连接线。默认为 None，表示没有箭头。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d4187d6-67ac-44a0-81aa-96399627cd32",
   "metadata": {},
   "source": [
    "mutation_scale：可选参数，用于指定箭头的大小缩放比例，默认为 1.0。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6df723fa-d44a-434d-9906-7cae2cd51438",
   "metadata": {},
   "source": [
    "color：可选参数，指定连接线的颜色，默认为黑色 'k'。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd8f8ddd-1493-435d-90fe-1fb51a0b0a5b",
   "metadata": {},
   "source": [
    "linewidth：可选参数，指定连接线的线宽，默认为 0.5。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f52036b-75e0-45f7-849d-324550f60347",
   "metadata": {},
   "source": [
    "linestyle：可选参数，指定连接线的线型，默认为 '‐'。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "825c1fb9-3750-44fe-a19e-615847d2aa04",
   "metadata": {},
   "source": [
    "zorder：可选参数，指定连接线的绘制顺序，数值越高，越在上层绘制，默认为 None。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca3f2ccb-3a34-445a-8acb-4f3ed0a25f98",
   "metadata": {},
   "source": [
    "其他参数：还可以设置其他一些参数，例如 facecolor、edgecolor 等，以自定义连接线的样式。\r\n",
    "通常，你需要指定连接线的起始点 xyA 和结束点 xyB，以及它们的坐标系 coordsA 和 coordsB。然后，可\r\n",
    "以设置连接线的样式、颜色、线宽等属性，以满足特定的需求。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36593978-37f5-431f-8e7c-91b1137ea42a",
   "metadata": {},
   "source": [
    "ConnectionPatch 主要用于在图中添加注释、连线、箭头等，帮助解释和可视化数据"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "041d5349-f8a3-4a80-98db-9821704d1769",
   "metadata": {},
   "source": [
    "3 进阶饼图-甜甜圈图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8886d079-68ec-45b2-8b71-d00d267a6cf2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotx\n",
    "\n",
    "with plt.style.context(matplotx.styles.pitaya_smoothie['light']):\n",
    "\n",
    "    # 创建一个图形窗口，设置大小和分辨率\n",
    "    plt.figure(figsize=(8,6),dpi=100)\n",
    "    plt.axis(\"equal\")  # 将x和y轴坐标轴的刻度范围设为相等\n",
    "    data = [375.0,75.0,250.0,300.0]\n",
    "    ingredients = ['面粉','糖','黄油','浆果']\n",
    "    # 自定义饼图格式函数\n",
    "    def func(pct,allvals):\n",
    "        absolute = int(np.round(pct / 100. * np.sum(allvals)))\n",
    "        '''\n",
    "        pct：这通常是一个介于 0 和 100 之间的浮点数，表示饼图中某个部分所占的百分比\n",
    "        np.sum(allvals)：这里 allvals 是一个包含所有部分数值的数组（在这个例子中，是配料的质量数组）。\n",
    "        np.sum(allvals) 计算这个数组中所有元素的和，即饼图所代表的总数值\n",
    "        pct / 100.：将百分比转换为小数。比如，如果 pct 是 50，那么 pct / 100. 的结果就是 0.5。\n",
    "        pct / 100. * np.sum(allvals)：将百分比转换为小数后，再乘以总和 np.sum(allvals)，\n",
    "        得到饼图中该部分所对应的绝对数值\n",
    "        np.round(...)：np.round 函数用于对结果进行四舍五入。\n",
    "        这是为了确保得到的绝对数值是一个整数（或指定的小数位数），这在显示时通常更直观\n",
    "        '''\n",
    "        return f\"{pct:.1f}%\\n({absolute:d}g)\"\n",
    "    # 创建饼图\n",
    "    wedges,texts,autotexts = plt.pie(data,autopct=lambda pct:func(pct,data),\n",
    "                                     # 使用自定义函数显示百分比和绝对值\n",
    "                                    textprops=dict(color=\"w\"),\n",
    "                                     radius=1,\n",
    "                                    labels=ingredients,)\n",
    "    # 创建一个小的白色饼图作为甜甜圈图的中心空白部分\n",
    "    plt.pie(data,radius=.3,colors=['white'])\n",
    "    # 添加图例\n",
    "    plt.legend(wedges,ingredients,loc=\"center left\",\n",
    "              bbox_to_anchor=(.96,0,0.5,1),prop={'family':'STsong','size':12},\n",
    "              title=\"配料\",title_fontproperties='STsong')\n",
    "    # 设置文本属性\n",
    "    plt.setp(autotexts,fontproperties='Times New Roman',size=8,weight=\"bold\",)\n",
    "    plt.setp(texts,fontproperties='STsong',size=8,weight='bold',)\n",
    "    # 设置标题\n",
    "    plt.title(\"matplotlib 烘焙坊：甜甜圈图\",fontproperties='STsong')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58061497-7bb8-41e4-92c8-27c51814be67",
   "metadata": {},
   "source": [
    "在 `plt.pie(data, autopct=lambda pct: func(pct, data), textprops=dict(color=\"w\"))`\r\n",
    "这行代码中，`wedges`、`texts` 和 `autotexts` 是由 `plt.pie()` 函数返回的元组，\r\n",
    "用于引用饼图的不同部分和文本标签。具体解释如下："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66d5054f-b8e9-4d76-9f96-ef6e1228421c",
   "metadata": {},
   "source": [
    "wedges`：这是一个饼图中扇形部分的集合。每个扇形代表数据中的一个部分，\n",
    "通常对应于饼图中的一个切片。`wedges` 是一个包含这些扇形的对象集合\r\n",
    "可以用于进一步设置它们的属性，例如颜色、边框等。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f916db0f-01b0-4a36-b272-86d3c2776833",
   "metadata": {},
   "source": [
    "texts`：这是一个饼图中扇形外部文本标签的集合。\n",
    "这些文本标签通常用于显示每个扇形的标签或描述。你可以使用 `texts\r\n",
    "来设置这些文本标签的属性，例如字体大小、颜色\r\n",
    "↩→"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d12f4658-859a-4ed7-a59b-5a21c620517b",
   "metadata": {},
   "source": [
    "autotexts`：这是一个饼图中扇形内部自动生成的文本标签的集合。\n",
    "这些文本标签通常用于显示每个扇形的百分比或数值。与 `texts` 类似，你可以使\r\n",
    "`autotexts` 来设置这些文本标签的属性，例如字体大小、颜色等"
   ]
  }
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